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多光谱成像在种子表型和质量监测中的最新应用概述。

Recent Applications of Multispectral Imaging in Seed Phenotyping and Quality Monitoring-An Overview.

机构信息

Department of Pharmacology & Toxicology, College of Pharmacy, King Saud University, Riyadh 11564, Saudi Arabia.

Faculty of Agriculture, Suez Canal University, Ring Road Km 4.5, Ismailia P.O. Box 41522, Egypt.

出版信息

Sensors (Basel). 2019 Mar 4;19(5):1090. doi: 10.3390/s19051090.

Abstract

As a synergistic integration between spectroscopy and imaging technologies, spectral imaging modalities have been emerged to tackle quality evaluation dilemmas by proposing different designs with effective and practical applications in food and agriculture. With the advantage of acquiring spatio-spectral data across a wide range of the electromagnetic spectrum, the state-of-the-art multispectral imaging in tandem with different multivariate chemometric analysis scenarios has been successfully implemented not only for food quality and safety control purposes, but also in dealing with critical research challenges in seed science and technology. This paper will shed some light on the fundamental configuration of the systems and give a birds-eye view of all recent approaches in the acquisition, processing and reproduction of multispectral images for various applications in seed quality assessment and seed phenotyping issues. This review article continues from where earlier review papers stopped but it only focused on fully-operated multispectral imaging systems for quality assessment of different sorts of seeds. Thence, the review comprehensively highlights research attempts devoted to real implementations of only fully-operated multispectral imaging systems and does not consider those ones that just utilized some key wavelengths extracted from hyperspectral data analyses without building independent multispectral imaging systems. This makes this article the first attempt in briefing all published papers in multispectral imaging applications in seed phenotyping and quality monitoring by providing some examples and research results in characterizing physicochemical quality traits, predicting physiological parameters, detection of defect, pest infestation and seed health.

摘要

作为光谱学和成像技术的协同集成,光谱成像模式已经出现,通过提出具有有效和实际应用的不同设计来解决质量评估难题,在食品和农业中。通过在宽电磁光谱范围内获取空间-光谱数据的优势,最先进的多光谱成像与不同的多元化学计量分析场景相结合,不仅成功地用于食品质量和安全控制目的,而且还用于解决种子科学和技术中的关键研究挑战。本文将介绍系统的基本结构,并概述所有最新方法,用于获取、处理和再现多光谱图像,以用于各种应用,如种子质量评估和种子表型问题。这篇综述文章是在早期综述文章的基础上进行的,但它只关注用于不同类型种子质量评估的全操作多光谱成像系统。因此,该综述全面强调了仅致力于全操作多光谱成像系统实际实现的研究尝试,而不考虑那些仅利用高光谱数据分析中提取的某些关键波长而不构建独立多光谱成像系统的研究尝试。这使得本文首次尝试简要介绍多光谱成像在种子表型和质量监测中的所有应用论文,提供一些示例和研究结果,用于描述物理化学质量特征、预测生理参数、检测缺陷、虫害和种子健康。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc3d/6427362/a5c2340524c4/sensors-19-01090-g001.jpg

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